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1.
Med Biol Eng Comput ; 55(6): 897-908, 2017 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-27638108

RESUMO

An algorithm for delineating complex head and neck cancers in positron emission tomography (PET) images is presented in this article. An enhanced random walk (RW) algorithm with automatic seed detection is proposed and used to make the segmentation process feasible in the event of inhomogeneous lesions with bifurcations. In addition, an adaptive probability threshold and a k-means based clustering technique have been integrated in the proposed enhanced RW algorithm. The new threshold is capable of following the intensity changes between adjacent slices along the whole cancer volume, leading to an operator-independent algorithm. Validation experiments were first conducted on phantom studies: High Dice similarity coefficients, high true positive volume fractions, and low Hausdorff distance confirm the accuracy of the proposed method. Subsequently, forty head and neck lesions were segmented in order to evaluate the clinical feasibility of the proposed approach against the most common segmentation algorithms. Experimental results show that the proposed algorithm is more accurate and robust than the most common algorithms in the literature. Finally, the proposed method also shows real-time performance, addressing the physician's requirements in a radiotherapy environment.


Assuntos
Neoplasias de Cabeça e Pescoço/diagnóstico , Tomografia por Emissão de Pósitrons/métodos , Algoritmos , Humanos , Processamento de Imagem Assistida por Computador/métodos , Imagens de Fantasmas
2.
Q J Nucl Med Mol Imaging ; 60(3): 264-73, 2016 09.
Artigo em Inglês | MEDLINE | ID: mdl-27463889

RESUMO

BACKGROUND: In this paper the clinical value of PET for early prediction of tumor response to erlotinib in patients with advanced or metastatic non-small cell lung cancer (NSCLC) after failure of at least one prior chemotherapy regimen is evaluated. The aim was to compare the early metabolic treatment response using European Organization for Research and Treatment of Cancer (EORTC) 1999 recommendations and PET Response Criteria in Solid Tumors (PERCIST), and the standard treatment response using Response Evaluation Criteria in Solid Tumors (RECIST). METHODS: Twenty patients with stage IV NSCLC were enrolled prospectively. PET/CT studies were performed before, then 48 hours, and 45 days after the initiation of erlotinib treatment. The lesion with the highest uptake in each patient was evaluated according to EORTC 1999 recommendations, PERCIST and RECIST to assess metabolic and anatomic response. Response classifications were compared statistically using Wilcoxon signed-rank test. Disease-free survival (DFS) and overall survival (OS) were calculated by the Kaplan-Meier Test. RESULTS: At 48 hours, the Kaplan-Meier analysis showed that EORTC proved to be a significant prognostic factor for predicting DFS and OS. At 45 days, there was a significant difference in response evaluation between RECIST and metabolic classifications. RECIST and PERCIST were significant prognostic factors for predicting DFS and OS. EORTC was not able to discriminate responder from non-responder patients. CONCLUSIONS: This study shows that, according to the EORTC protocol, the PET exam is able to provide early identification of patients who benefit from Erlotinib treatment. Used at the end of therapy, PERCIST could be considered an appropriate metabolic evaluation method to discriminate responders from non-responders.


Assuntos
Antineoplásicos/uso terapêutico , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Cloridrato de Erlotinib/uso terapêutico , Neoplasias Pulmonares/tratamento farmacológico , Adulto , Idoso , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Intervalo Livre de Doença , Feminino , Humanos , Estimativa de Kaplan-Meier , Neoplasias Pulmonares/mortalidade , Masculino , Pessoa de Meia-Idade , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Estudos Prospectivos , Fatores de Tempo , Resultado do Tratamento
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